Definition, sourcing, and updating of the emissions baselines

In this technical document, we explain the methods used to generate the emissions baselines in the Climate Equity Reference Calculator. Before doing so, it’s extremely helpful to review the baseline-related challenges raised by the effort-sharing problem.

The key point is that effort-sharing frameworks (as opposed to resource-sharing frameworks that divide up, say, a fixed emissions budget) require baselines. This is because “effort” must be measured against a baseline, and – by definition – it should be a “no effort” or “no policies” baseline. There are two distinct challenges here.

First, any generalized effort-sharing framework requires emissions baselines for all countries, as well as projections of other constituent indicators including GDP, emissions intensity, and population. And these projections, to be policy relevant, must extend out at least as far as 2030. However, except for population,[1] there are no widely-used country-level projections for these baselines and indicators that extend out beyond a few years.

Second, as anyone who has investigated the problem of baseline modeling is well aware, widely known and properly vetted “no effort” baselines are simply not available “off the shelf.”

Given these challenges, we have been forced to contrive our own baselines, and this despite the fact that we claim no special expertise in making long-term projections. Our basic rule, therefore, has been minimalism. We have avoiding making up numbers wherever we possibly could, and have rather relied as heavily as possible on existing, widely known and well vetted projections for all key indicators, which we’ve done by updating these projections for the recent history that has transpired since they were published.

When doing this updating, we have been forced to make a few assumptions. For example, we’ve chosen to “smooth” historical data when merging it with projected data to avoid any unrealistically abrupt transitions. And (like others before us) we have used “downscaling” methods to derive plausible national estimates from pre-existing analyses that are aggregated at the regional level.

More specifically, we combine recent historical GDP and CO2 emission intensity growth rates with projected growth rates from the IMF [2] (for near term GDP growth) and IPCC [3] (for projections of longer-term GDP growth and emission intensity changes), to produce annualized projections of future GDP and CO2 emissions intensity. The product of the projected GDP and CO2 emission intensity yields national CO2 emission pathways. For non-CO2 emissions, we also use projected growth rates from IPCC.[3]

And what about the need for “no effort” or “policy free” baselines?

The problem here is comparability of effort. Which is to say that all countries – whether wealthy or developing or somewhere in between – must have the same kind of baselines if comparability of effort is to be possible. Again, this is because mitigation effort can only be calculated as reduction below an emissions baseline. The ideal emissions baseline is a counter-factual one in which no policies that effect emissions (whether these be explicitly climate policies or not) are included, for then all current policies – when extended forward – would be counted as effort. Only then are apples, as it were, compared to apples.

The situation here is actually rather odd. For example, some people believe that our baselines are unreasonably high, and this is particularly true in European countries that have made substantial effort to reduce their domestic emissions. However, there is a “be careful what you wish for” element to this situation. If future effort in these countries is calculated on the basis of baselines which already contain all current policies (as is for example done in the IEA’s World Energy Outlook), then future efforts will appear to be altogether and even absurdly inadequate. It’s only by measuring all efforts against a counter-factual, no-policies baseline that the real truth of the situation – for example, that northern European countries are already doing significant mitigation – becomes visible.

Does this mean that we ourselves calculate counter-factual no-policies baselines? We do not. After all, there are good reasons why such baselines are not readily available (although in the past the SRES scenarios often served that purpose). For example, even if it were possible to define emissions baselines that exclude all explicit climate policies, there are a myriad of other policies – gasoline taxes, fuel efficiency standards, and so on – which require substantive effort and which produce climate benefits, even though they are often not motivated by a desire for climate action.

Given all this, our strategy is a modest one. As we mention above and explain in greater detail below, our algorithm for projecting CO2 emissions is based on combining estimates of emissions intensity reduction with estimates of GDP growth, with the values for both derived from a convergence from historical rates of change to projected long-term (through 2030) rates of change. To limit the influence of climate policies, we have elected to utilize the rates of change for GDP and emissions intensity from a set of baseline scenarios that are included in the scenario database of the IPCC’s Fifth Assessment report (the baseline scenarios of the EMF27 modelling exercise, to be precise)

[1] The UN Population Division’s “Medium Variant,” which has projections to 2100 for all countries and a world population of 9.5 billion in 2050, has effectively cornered the market for BAU population projections, and who are we to argue with the market? Available at http://www.un.org/en/development/desa/population/
[2] The IMF’s biannual World Economic Outlook includes projections for the next five years for most countries. Available at http://www.imf.org/external/pubs/ft/weo/2015/01/index.htm.
[3] Specifically, we are using the models in the EMF27Base-FullTech scenario as reported in the scenario database of the IPCC’s Fifth Assessment Report, which can be found at https://secure.iiasa.ac.at/web-apps/ene/AR5DB